AMD EPYC 3255 8-Core Temp testing with a congatec conga-B7E3 (5.13 BIOS) and MSI NVIDIA GeForce GTX 1050 2GB on Ubuntu 16.04 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2106294-IB-SS497779426
ss,
"Sysbench 1.0.20 - Test: CPU",
Higher Results Are Better
"sysbench1604Ph10",12118.33,12006.55,11929.65
"Algebraic Multi-Grid Benchmark 1.2 - ",
Higher Results Are Better
"amg1604Ph10",97942090,97789150,97813680
"GraphicsMagick 1.3.33 - Operation: Swirl",
Higher Results Are Better
"graphics-magick1604Ph10",289,287,286
"GraphicsMagick 1.3.33 - Operation: Rotate",
Higher Results Are Better
"graphics-magick1604Ph10",459,454,460
"GraphicsMagick 1.3.33 - Operation: Sharpen",
Higher Results Are Better
"graphics-magick1604Ph10",
"GraphicsMagick 1.3.33 - Operation: Enhanced",
Higher Results Are Better
"graphics-magick1604Ph10",121,120,120
"GraphicsMagick 1.3.33 - Operation: Resizing",
Higher Results Are Better
"graphics-magick1604Ph10",580,579,579
"GraphicsMagick 1.3.33 - Operation: Noise-Gaussian",
Higher Results Are Better
"graphics-magick1604Ph10",
"GraphicsMagick 1.3.33 - Operation: HWB Color Space",
Higher Results Are Better
"graphics-magick1604Ph10",710,712,710
"RAMspeed SMP 3.5.0 - Type: Add - Benchmark: Integer",
Higher Results Are Better
"ramspeed1604Ph10",11130.58,11105.91,11108.65
"RAMspeed SMP 3.5.0 - Type: Scale - Benchmark: Integer",
Higher Results Are Better
"ramspeed1604Ph10",9692.29,9583.02,9689.21
"RAMspeed SMP 3.5.0 - Type: Average - Benchmark: Integer",
Higher Results Are Better
"ramspeed1604Ph10",10347.39,10349.2,10404.08
"RAMspeed SMP 3.5.0 - Type: Add - Benchmark: Floating Point",
Higher Results Are Better
"ramspeed1604Ph10",11138.12,11119.26,11110.53
"RAMspeed SMP 3.5.0 - Type: Scale - Benchmark: Floating Point",
Higher Results Are Better
"ramspeed1604Ph10",9822.86,9826.42,9807.47
"RAMspeed SMP 3.5.0 - Type: Average - Benchmark: Floating Point",
Higher Results Are Better
"ramspeed1604Ph10",10482.47,10483.92,10499.62
"CacheBench - Test: Read",
Higher Results Are Better
"cachebench1604Ph10",2093.754666,2088.80048,2078.329276
"CacheBench - Test: Write",
Higher Results Are Better
"cachebench1604Ph10",10882.233727,10824.277603,10888.675585
"CacheBench - Test: Read / Modify / Write",
Higher Results Are Better
"cachebench1604Ph10",21675.364993,21560.932226,21683.368482
"IPC_benchmark - Type: TCP Socket - Message Bytes: 128",
Higher Results Are Better
"ipc-benchmarking1604Ph10",1929212,1936815,1944382
"IPC_benchmark - Type: Unnamed Pipe - Message Bytes: 128",
Higher Results Are Better
"ipc-benchmarking1604Ph10",1910985,1929711,1937763
"IPC_benchmark - Type: FIFO Named Pipe - Message Bytes: 128",
Higher Results Are Better
"ipc-benchmarking1604Ph10",1805751,1780572,1848108
"IPC_benchmark - Type: Unnamed Unix Domain Socket - Message Bytes: 128",
Higher Results Are Better
"ipc-benchmarking1604Ph10",873693,915806,1289328,1051305,1231102,878949,879742,937926,973551,871193,879381,1351189,880751,1140666,876021
"IPC_benchmark - Type: TCP Socket - Message Bytes: 1024",
Higher Results Are Better
"ipc-benchmarking1024-1604Ph10",1484242,1480274,1464625
"IPC_benchmark - Type: Unnamed Pipe - Message Bytes: 1024",
Higher Results Are Better
"ipc-benchmarking1024-1604Ph10",1653163,1666142,1621781
"IPC_benchmark - Type: FIFO Named Pipe - Message Bytes: 1024",
Higher Results Are Better
"ipc-benchmarking1024-1604Ph10",1596776,1570983,1602704
"IPC_benchmark - Type: Unnamed Unix Domain Socket - Message Bytes: 1024",
Higher Results Are Better
"ipc-benchmarking1024-1604Ph10",1508941,1502603,1484107
"SciMark 2.0 - Computational Test: Composite",
Higher Results Are Better
"scimark1604Ph10",386.72,374.96,387.04
"SciMark 2.0 - Computational Test: Monte Carlo",
Higher Results Are Better
"scimark1604Ph10",101.16,102.1,101.16
"SciMark 2.0 - Computational Test: Fast Fourier Transform",
Higher Results Are Better
"scimark1604Ph10",166.75,168.31,166.41
"SciMark 2.0 - Computational Test: Sparse Matrix Multiply",
Higher Results Are Better
"scimark1604Ph10",499.31,502.49,499.05
"SciMark 2.0 - Computational Test: Dense LU Matrix Factorization",
Higher Results Are Better
"scimark1604Ph10",312.49,316.83,315.09
"SciMark 2.0 - Computational Test: Jacobi Successive Over-Relaxation",
Higher Results Are Better
"scimark1604Ph10",853.9,785.08,853.52
"Apache Benchmark 2.4.29 - Static Web Page Serving",
Higher Results Are Better
"apache-ctx_clock1604Ph10",19704.78,19548.68,19122.65
"NAS Parallel Benchmarks 3.4 - Test / Class: EP.C",
Higher Results Are Better
"npb1604Ph10",222.07,220.8,221.1
"NAS Parallel Benchmarks 3.4 - Test / Class: EP.D",
Higher Results Are Better
"npb1604Ph10",218.31,216.74,216.61
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",17.9551,17.7416,17.5803
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",18.6203,18.5901,18.5678
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",9.78849,9.77523,9.77334
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",4.86462,4.86344,4.86229
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",38.3038,38.3174,38.3015
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",14.5489,14.6491,14.6321
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",21.0188,21.0447,20.858
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",43.9534,43.9552,43.9027
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",10.2266,10.2658,10.2651
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",13.767,13.9382,13.7732
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",12184.9,12260.2,12318.7
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",8575.11,8560.74,8604.11
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",12263.8,12359.8,12319
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",8551.77,8593.38,8587.55
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",10.7502,10.7486,10.9213
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",12266,12212.5,12309.2
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",8545.81,8618.86,8552.8
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"onednn1604Ph10",6.42701,6.41209,6.41484